<!DOCTYPE html>
<html lang="zh-CN">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>机器学习与搜索技术的智能融合</title>
    <link href="https://cdn.staticfile.org/font-awesome/6.4.0/css/all.min.css" rel="stylesheet">
    <link href="https://cdn.staticfile.org/tailwindcss/2.2.19/tailwind.min.css" rel="stylesheet">
    <link href="https://fonts.googleapis.com/css2?family=Noto+Serif+SC:wght@400;500;600;700&family=Noto+Sans+SC:wght@300;400;500;700&display=swap" rel="stylesheet">
    <script src="https://cdn.jsdelivr.net/npm/mermaid@latest/dist/mermaid.min.js"></script>
    <style>
        body {
            font-family: 'Noto Sans SC', Tahoma, Arial, Roboto, "Droid Sans", "Helvetica Neue", "Droid Sans Fallback", "Heiti SC", "Hiragino Sans GB", Simsun, sans-serif;
            background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
            min-height: 100vh;
        }
        
        .hero-gradient {
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
        }
        
        .card-hover {
            transition: all 0.3s ease;
            border: 1px solid transparent;
        }
        
        .card-hover:hover {
            transform: translateY(-5px);
            box-shadow: 0 20px 40px rgba(0,0,0,0.1);
            border-color: #667eea;
        }
        
        .text-gradient {
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            -webkit-background-clip: text;
            -webkit-text-fill-color: transparent;
            background-clip: text;
        }
        
        .section-title {
            position: relative;
            padding-left: 20px;
        }
        
        .section-title::before {
            content: '';
            position: absolute;
            left: 0;
            top: 50%;
            transform: translateY(-50%);
            width: 4px;
            height: 30px;
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            border-radius: 2px;
        }
        
        .feature-icon {
            width: 60px;
            height: 60px;
            display: flex;
            align-items: center;
            justify-content: center;
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            border-radius: 15px;
            color: white;
            font-size: 24px;
            margin-bottom: 20px;
        }
        
        .mermaid {
            background: white;
            padding: 30px;
            border-radius: 15px;
            box-shadow: 0 10px 30px rgba(0,0,0,0.1);
        }
        
        .drop-cap {
            float: left;
            font-size: 4em;
            line-height: 0.8;
            margin: 0.1em 0.1em 0 0;
            font-weight: 700;
            color: #667eea;
        }
        
        .highlight-box {
            background: linear-gradient(135deg, rgba(102, 126, 234, 0.1) 0%, rgba(118, 75, 162, 0.1) 100%);
            border-left: 4px solid #667eea;
            padding: 20px;
            margin: 20px 0;
            border-radius: 0 10px 10px 0;
        }
        
        @keyframes fadeInUp {
            from {
                opacity: 0;
                transform: translateY(30px);
            }
            to {
                opacity: 1;
                transform: translateY(0);
            }
        }
        
        .animate-fadeInUp {
            animation: fadeInUp 0.8s ease-out;
        }
    </style>
</head>
<body>
    <!-- Hero Section -->
    <section class="hero-gradient text-white py-20 px-6">
        <div class="max-w-6xl mx-auto text-center animate-fadeInUp">
            <h1 class="text-5xl md:text-6xl font-bold mb-6">
                机器学习与搜索技术的智能融合
            </h1>
            <p class="text-xl md:text-2xl mb-8 opacity-90">
                探索AI驱动的下一代搜索引擎技术
            </p>
            <div class="flex justify-center space-x-4">
                <div class="bg-white bg-opacity-20 backdrop-blur-sm rounded-full px-6 py-3">
                    <i class="fas fa-brain mr-2"></i>智能理解
                </div>
                <div class="bg-white bg-opacity-20 backdrop-blur-sm rounded-full px-6 py-3">
                    <i class="fas fa-search mr-2"></i>精准搜索
                </div>
                <div class="bg-white bg-opacity-20 backdrop-blur-sm rounded-full px-6 py-3">
                    <i class="fas fa-user-cog mr-2"></i>个性推荐
                </div>
            </div>
        </div>
    </section>

    <!-- Main Content -->
    <main class="max-w-6xl mx-auto px-6 py-12">
        
        <!-- Introduction -->
        <section class="bg-white rounded-2xl shadow-xl p-8 md:p-12 mb-12 animate-fadeInUp">
            <h2 class="text-3xl font-bold mb-6 section-title">引言</h2>
            <p class="text-lg leading-relaxed text-gray-700">
                <span class="drop-cap">在</span>当今信息爆炸的时代，用户需要在海量的数据中快速、准确地找到所需的信息。传统的搜索技术主要基于关键词匹配，虽然能够在一定程度上满足用户的需求，但对于语义理解、上下文关联等方面的处理能力有限。而机器学习技术的发展为搜索技术带来了新的机遇，通过将机器学习和搜索技术相结合，可以构建出更加智能、高效的搜索系统，提升用户的搜索体验。
            </p>
        </section>

        <!-- Key Integration Points -->
        <section class="mb-12">
            <h2 class="text-3xl font-bold mb-8 text-center text-gradient">机器学习与搜索技术的结合点</h2>
            <div class="grid md:grid-cols-3 gap-6">
                <div class="bg-white rounded-xl shadow-lg p-6 card-hover">
                    <div class="feature-icon">
                        <i class="fas fa-language"></i>
                    </div>
                    <h3 class="text-xl font-bold mb-3">语义理解</h3>
                    <p class="text-gray-600">
                        传统搜索基于关键词匹配，无法理解用户输入的语义。机器学习中的NLP技术可以对文本进行语义分析，通过词向量模型将词语映射到低维向量空间，计算词语相似度，深度理解用户意图。
                    </p>
                </div>
                <div class="bg-white rounded-xl shadow-lg p-6 card-hover">
                    <div class="feature-icon">
                        <i class="fas fa-user-circle"></i>
                    </div>
                    <h3 class="text-xl font-bold mb-3">个性化推荐</h3>
                    <p class="text-gray-600">
                        通过分析用户的历史行为数据，如搜索记录、点击记录等，为用户提供个性化的搜索结果。协同过滤算法可以找到兴趣相似的用户群体，基于相似用户的搜索历史推荐相关内容。
                    </p>
                </div>
                <div class="bg-white rounded-xl shadow-lg p-6 card-hover">
                    <div class="feature-icon">
                        <i class="fas fa-expand-arrows-alt"></i>
                    </div>
                    <h3 class="text-xl font-bold mb-3">查询扩展与优化</h3>
                    <p class="text-gray-600">
                        机器学习可以分析用户查询，挖掘潜在查询意图。通过分类算法将查询分类到不同领域，提供相关查询建议；通过排序算法重新排序搜索结果，将更符合用户需求的结果优先展示。
                    </p>
                </div>
            </div>
        </section>

        <!-- Implementation Methods -->
        <section class="bg-white rounded-2xl shadow-xl p-8 md:p-12 mb-12">
            <h2 class="text-3xl font-bold mb-8 section-title">实践方法</h2>
            
            <div class="space-y-8">
                <div class="highlight-box">
                    <h3 class="text-xl font-bold mb-3 flex items-center">
                        <i class="fas fa-database mr-3 text-purple-600"></i>数据准备
                    </h3>
                    <div class="grid md:grid-cols-3 gap-4 mt-4">
                        <div class="bg-white rounded-lg p-4">
                            <strong class="text-purple-600">用户行为数据</strong>
                            <p class="text-sm text-gray-600 mt-1">搜索记录、点击记录、浏览记录等，反映用户兴趣和需求</p>
                        </div>
                        <div class="bg-white rounded-lg p-4">
                            <strong class="text-purple-600">文档数据</strong>
                            <p class="text-sm text-gray-600 mt-1">被搜索的文档数据，包括标题、内容等信息</p>
                        </div>
                        <div class="bg-white rounded-lg p-4">
                            <strong class="text-purple-600">标注数据</strong>
                            <p class="text-sm text-gray-600 mt-1">监督学习任务所需的分类、标注等数据</p>
                        </div>
                    </div>
                </div>

                <div class="highlight-box">
                    <h3 class="text-xl font-bold mb-3 flex items-center">
                        <i class="fas fa-filter mr-3 text-purple-600"></i>特征提取
                    </h3>
                    <ul class="space-y-2">
                        <li class="flex items-start">
                            <i class="fas fa-check-circle text-purple-600 mr-2 mt-1"></i>
                            <div>
                                <strong>词袋模型：</strong>将文本表示为词的集合，每个词作为一个特征，计算词频等信息
                            </div>
                        </li>
                        <li class="flex items-start">
                            <i class="fas fa-check-circle text-purple-600 mr-2 mt-1"></i>
                            <div>
                                <strong>TF-IDF：</strong>考虑词在文本中的频率以及在整个语料库中的逆文档频率
                            </div>
                        </li>
                        <li class="flex items-start">
                            <i class="fas fa-check-circle text-purple-600 mr-2 mt-1"></i>
                            <div>
                                <strong>词向量：</strong>使用预训练模型将词语映射到低维向量空间，捕捉语义关系
                            </div>
                        </li>
                    </ul>
                </div>

                <div class="highlight-box">
                    <h3 class="text-xl font-bold mb-3 flex items-center">
                        <i class="fas fa-robot mr-3 text-purple-600"></i>模型选择与训练
                    </h3>
                    <div class="grid md:grid-cols-3 gap-4 mt-4">
                        <div class="text-center">
                            <i class="fas fa-tags text-3xl text-purple-600 mb-2"></i>
                            <h4 class="font-bold">分类模型</h4>
                            <p class="text-sm text-gray-600">朴素贝叶斯、SVM等</p>
                        </div>
                        <div class="text-center">
                            <i class="fas fa-project-diagram text-3xl text-purple-600 mb-2"></i>
                            <h4 class="font-bold">聚类模型</h4>
                            <p class="text-sm text-gray-600">K-Means、DBSCAN等</p>
                        </div>
                        <div class="text-center">
                            <i class="fas fa-thumbs-up text-3xl text-purple-600 mb-2"></i>
                            <h4 class="font-bold">推荐模型</h4>
                            <p class="text-sm text-gray-600">协同过滤、矩阵分解等</p>
                        </div>
                    </div>
                </div>
            </div>
        </section>

        <!-- System Architecture Visualization -->
        <section class="mb-12">
            <h2 class="text-3xl font-bold mb-8 text-center text-gradient">系统架构图</h2>
            <div class="mermaid">
                graph TB
                    A[用户查询] --> B[查询理解模块]
                    B --> C[语义分析]
                    B --> D[意图识别]
                    C --> E[特征提取]
                    D --> E
                    E --> F[机器学习模型]
                    F --> G[结果排序]
                    F --> H[个性化推荐]
                    G --> I[搜索结果]
                    H --> I
                    J[用户行为数据] --> K[数据处理]
                    K --> F
                    L[文档数据库] --> M[索引构建]
                    M --> F
                    
                    style A fill:#667eea,stroke:#fff,stroke-width:2px,color:#fff
                    style I fill:#764ba2,stroke:#fff,stroke-width:2px,color:#fff
                    style F fill:#f093fb,stroke:#fff,stroke-width:2px,color:#fff
            </div>
        